1. Field of the Invention
This invention relates to the arts of imaging and image processing, including sensor design and moiré reduction technologies.
2. Background of the Invention
Well-known imaging technologies include film (e.g. analog), digital, and analog-digital hybrid approaches. Film imaging processes use a set of lenses to focus an image onto a film sheet which is impregnated with grains of material reactive to the spectrum to be recorded, such as visible light, infrared (“IR”), or X-ray. The grains are randomly arranged in each sheet of film, and thus reproduction of the image on the developed film has a certain resolution based on the size and density of these grains.
In digital imaging, a sensor of uniformly-arranged sensing elements is used to capture “bits” or pixels of the image. Turning to FIG. 1, the system components (10) of a typical digital camera are shown. In this example, a scene or original item (1) is digitally imaged using a two-dimensional array (7) of sensors such as an array of charge-coupled devices (“CCD”). The image of the scene is focused onto the array (7) by a lens (6), and a shutter (not shown) may be used to provided a specific duration of exposure. The sensor elements are arranged with uniform spacing into rows and columns.
Turning to FIG. 2, more details of a typical two-dimensional sensor array (7) are shown. The sensor element columns are uniformly spaced at distance d1 from each other according to a linear function such as:x-axis position of sensor in column n=Pn=(n−1)·d1where the array is comprised of N sensor columns, n is the column number ranging from 1 through N, and d1 is the uniform distance between the sensor columns.
Likewise, the sensor element rows are uniformly spaced at distance d2 from each other according to a linear function such as:y-axis position of sensor in column m=Pm=(m−1)·d2where the array is comprised of M sensor rows, m is the row number ranging from 1 through M, and d2 is the uniform distance between the sensor rows.
In many two-dimensional sensor arrays, the row-to-row spacing d1 may be equal to the column-to-column spacing d2. The number of columns N may be equal to the number of columns M, as well.
The sensors may in practice be reactive to any range of electromagnetic (“EM”) spectrum according to the desired application, such as charge-coupled devices (“CCD”) for visible or IR imaging.
Typically, the voltage level on each sensor element is measured and converted (e.g. sampled) to a digital value using an analog-to-digital converter. The sample value is relative to the amount of electromagnetic energy incident on the sensor element. Conversion to digital values are typically performed using an analog-to-digital converter having sufficient resolution (e.g. data width) for the intended application. The digital data set (66) of samples represents a digitized or pixelated copy of the image.
Additionally, mechanical and/or chemical filtering and band separation of the EM spectrum may be performed to produced “separated” data sets, such as use of a color wheel in front of the sensor array, or placement of color filters over the sensor elements themselves.
Moiré patterns are artifacts of certain imaging processes which are perceptible to the human eye, but do not represent actual features or details in the original item imaged. They often resemble crosshatch halftones across all or a portion of a digital image.
For imaging processes in which the original is an analog image, for example a photographic subject, moiré patterns may appear when certain features align with the sensors in the sensor array. For example, a digital photograph of a bug screen on a window often produces noticeable moiré patterns due to the bug screen's uniform grid-like features. The resulting apparent pattern is actually an interference pattern between the physical spacing of features of the original image and the spacing of the sensor array.
Just as in the phenomena of interference patterns between other types of signals, visual moiré patterns may become apparent at “harmonics” or integral multiples of spacing distances of the original image features and the spacing distances of the sensor array. For example, if the repeating features of a photographic subject are focussed onto two-dimensional sensor array having a sensor spacing of 600 dots per inch (“DPI”) and a moiré pattern forms, then the same image focused at the same distance on a sensor array having a sensor spacing of 1200 DPI will likely result in the appearance of moiré patterns. Undersampling the image at 300 DPI would also likely result in the appearance of moiré patterns.
Many techniques have been developed to try to reduce moiré patterns which appear in existing digital images, such as application of image processing techniques including Gaussian blurring, “descreening” algorithms, and “de-speckle” processes. Most of these have a result of reducing the sharpness of the overall image because they reduce the moiré pattern by spreading energy or brightness from a given pixel to adjacent pixels.
As discussed in the related applications in an example as shown in FIG. 3a, pixel N represents a pixel of a moiré pattern in a single row or column, and in this case, a pattern which is darker than the surrounding pixels, N−1 and N+1. The energy E2 of pixel N is lower than the energy E3 of the adjacent pixels N+1 and N−1. A blurring process applies a partial or weighted averaging among regional or adjacent pixels, such as shown in FIG. 3b, wherein the energy of the pixel in the moiré pattern is slightly increased to E2′, and the energy of the adjacent pixels are slightly decreased to E3′.
While this oftentimes decreases the obviousness or appearance of the moiré pattern to the human observer, it also reduces the “sharpness” or level of apparent detail of the entire image. If the blurring process is applied manually on a regional basis, the degradation to the entire image may be avoided, but the local areas are still degraded and substantial human intervention may be required to do so. Additionally, “edge effects” may become perceptible where the region of processing meets a region of unprocessed image.
So, to date, most digital image post-processing attempts to reduce moiré patterns either result in image degradation, require substantial human operator effort, or both to some degree.
A common technique employed to avoid the generation of moiré patterns in the imaging process is to mechanically move or “jitter” the sensor array such that the array is moved in physical position with respect to the original subject being imaged. In FIG. 4, such a jittering imaging system with a two-dimensional sensor array (7) is shown. An x-axis mechanical jitter drive (40) is coupled to the array (7) such that it's x-axis position is varied slightly over time, usually in a sinusoidal or triangular pattern (41). Likewise, a y-axis jitter drive (42) may jitter the array in an orthogonal direction, also typically in a sinusoidal or triangular pattern (43).
This jittering action allows the array (7) to scan a pattern of points which are not simply an array of uniformly spaced rows and columns, but which represent positions relative to the jittering functions Px′(t) and Py′(t). As such, fewer original image sources will have an interference pattern with the dithered sensor pattern, but it is still possible that portions of the original image source may interfere with the dithered sensor pattern to cause localized moiré patterns. Additionally, such jittering mechanisms tend to add expense and failure rate to an assembly such as a digital camera.
In the related applications, a system and method were disclosed which avoids generation of moiré patterns in digital images created with a two-dimensional sensor array, without the use of mechanical jittering mechanisms, intensive image post-processing technologies, or a high degree of human operator manipulation and editing. This new system and method maintained image quality while being readily realizable using current sensor technology, and to preferrably be compatible with widely-used image compression and decompression technologies such as bitmap, JPEG (joint photographic experts) and MPEG image products.
These related inventions provided a means for avoiding moiré patterns in digitized images by employing a two-dimensional sensor array of non-uniformly spaced sensors. This allows the spacing of the sensors to avoid having an inherent “frequency” that may interfere with details or harmonics present in the image source, which eliminates the occurrence of moiré patterns and the need for application of image processing to remove moiré patterns.
Using the related invention, the sensors are placed along a each axis in a non-uniform pseudorandom manner according to a predetermined scheme or function. During imaging, sensors are sampled and stored into a data set which represents non-uniformly spaced image points within the original image, scene or subject. Finally, linear interpolation is preferrably applied to the non-uniformly spaced data set to yield a synthesized uniformly-spaced data set for use in common imaging formats and processing, such as JPEG or MPEG compression and decompression.
Sensor elements, or “picture elements” (“pixels”), known in the art vary widely in size, geometry, dark current, sensitivity, dynamic range or gain, and EM band response, according to the semiconductor processes used to realize them and the specific structural design of the element. For example, some pixel elements are approximately 8 μm square, while others are as large as 10 μm or larger. Some pixel elements have extremely low dark currents or wide dynamic range, while still others may possess unusually flat response over a wide range of the EM spectrum, or are specifically enhanced for certain bands of the EM spectrum (e.g. infrared sensors). Pixel size also relates to the resolution or “sharpness” of the captured and digitized image, wherein larger pixel structures usually yield lower resolution images.
Arrays available on the market tend only to comprise one specific pixel type or another, and thus the entire array shares the same general characteristics, advantages, and specifications within some tolerance.
However, as was demonstrated in the related patent application, due to the non-uniform placement of pixels in the anti-moiré, significant unused array space between pixels may be produced in some combinations of 2, 3 or 4 adjacent pixels.
This provides an opportunity to potentially place smaller pixels between the larger pixels in order to increase the number of pixels within the array, and potentially add a second (or more) set of characteristics, advantages, and specifications to the array. In some cases, it may be desirable to “fill in” the gaps with smaller pixels of similar performance characteristics as the larger ones, and in other cases, it may be desirable to fill in the gaps with smaller pixels of dramatically different characteristics.
For example, for an intelligence gathering application wherein visible spectrum images are often compared with similar infrared (“IR”) images which were taken using 2 separate imaging systems, it may be desirable to realize an array having both types of pixels in the same array. By managing the focussing optics for separate “shots” but using a single imaging array (e.g. mechanically switching between one optics set to another), high correlation between the two spectrum images may be obtained which avoids parallax effects of using two separate cameras.
In another example for a medical imaging application, one pixel set of IR-sensitive elements may be overlaid with another pixel set of X-ray-sensitive pixels to yield highly correlated image data sets.
In general, this opportunity to “fill in” unused array space with smaller sensors or pixels did not exist until the inventions of the related patent applications were made. It is also important to note that the related patent applications disclose methods and systems for non-uniformly and pseudorandomly distributing sensor elements on sensor arrays, as well as display elements (TFT, LED's, etc.) on display arrays.
Therefore, there is a need in the art for a system and method which allows the unused array space in arrays of sensors and display elements to be used to host smaller sensor or display elements in order to realize unique advantages and functionality of the arrays. Further, there is a need in the art for this system and method to support the physically overlaid arrays to be of different technologies and performance characteristics, such that multiple, highly correlated data sets may be obtained from or displayed with a single physical sensor or display array.